Research

My research focuses on the theoretical aspects of algorithms, computational geometry, and machine learning. 

Papers

In the tradition of theoretical computer science, authors are listed in alphabetical order. Exceptions are marked with an asterisk (*), which indicates that the authors are listed by their level of contribution.

• Agnostic Active Learning of Single Index Models with Linear Sample Complexity
  Aarshvi Gajjar, Chinmay Hegde, Yi Li, Christopher Musco, Wai Ming Tai, Xingyu Xu
  Conference on Learning Theory (COLT) 2024

• Optimal Estimation of Gaussian (Poly)trees
  Yuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya *
  International Conference on Artificial Intelligence and Statistics (AISTATS) 2024

• Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models
  Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam *
  International Conference on Artificial Intelligence and Statistics (AISTATS) 2024

• Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures
  Bryon Aragam, Wai Ming Tai
  Conference on Learning Theory (COLT) 2023

• Learning Mixtures of Gaussians with Censored Data
  Wai Ming Tai, Bryon Aragam *
  International Conference on Machine Learning (ICML) 2023

• Optimal Coreset for Gaussian Kernel Density Estimation
  Wai Ming Tai
  Symposium on Computational Geometry (SOCG) 2022

• Optimal Estimation of Gaussian DAG Models
  Ming Gao, Wai Ming Tai, Bryon Aragam *
  International Conference on Artificial Intelligence and Statistics (AISTATS) 2022

• Finding an Approximate Mode of a Kernel Density Estimate
  Jasper C.H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai
  European Symposium on Algorithms (ESA) 2021

• The GaussianSketch for Almost Relative Error Kernel Distance
  Jeff M. Phillips, Wai Ming Tai
  International Conference on Randomization and Computation (RANDOM) 2020

• Approximate Guarantees for Dictionary Learning
  Aditya Bhaskara, Wai Ming Tai
  Conference on Learning Theory (COLT) 2019

• Near-Optimal Coresets of Kernel Density Estimates
  Jeff M. Phillips, Wai Ming Tai
  Symposium on Computational Geometry (SOCG) 2018 (Invited to DCG Special Issue)
  Discrete & Computational Geometry (DCG) 2020

• Improved Coresets for Kernel Density Estimates
  Jeff M. Phillips, Wai Ming Tai
  Symposium on Discrete Algorithms (SODA) 2018

• Tracking the Frequency Moments at All Times
  Zengfeng Huang, Wai Ming Tai, Ke Yi
  Unpublished

Academic Service

Program Committee for: ALT 2024

Reviewer for: NeurIPS 2024, ICML 2024, AISTATS 2024, ICLR 2024, SODA 2024, ESA 2023, NeurIPS 2023, FOCS 2023, ICML 2023, SOCG 2023, STOC 2023, SODA 2023, NeurIPS 2022, ESA 2022, ICALP 2022, SOCG 2020, ESA 2019